Search relevance in business intelligence systems through networked ranking

ABSTRACT

Method and system for optimizing search results in a business intelligence system. An member is selected in the business intelligence system having a user space, a content space, a data space, a master-data space and a metadata space. A relationship is determined between the member and a plurality of objects in the user space, the content space, the data space, the master-data space, or the metadata space. A ranking of the member is calculated based on the relationship. A relevance of the member in the business intelligence system is calculated using the ranking, thereby optimizing search results of the business intelligence system using the relevance of the object.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to and claims priority from U.S. Provisional Application Ser. No. 61/052,760, filed on May 13, 2008, entitled “Method and System For Improved Search Relevance in Business Intelligence and Related Unstructured Systems Through Networked Ranking” by Graham Mackintosh and Andrew Kowal, the entire disclosure of which is hereby incorporated by reference for all purposes as if fully set forth herein.

BACKGROUND

The present patent disclosure relates to the field of business intelligence and more particularly to the improvement of relevance of search results for business intelligence content.

Many businesses now generate and store information relating to all facets of the business. This information is often stored in data warehouse and databases. The amount of information stored can make finding relevant information difficult. However, timely intelligence is critical to proper business decision making.

A key to success in business today is therefore to understand and effectively manage the factors that drive an enterprise—a field known as business intelligence. Having critical Information about such business drivers allows decisions that will significantly improve results.

To facilitate better business intelligence decisions, organizations have developed data warehouses, which organize and link important customer information from a variety of data stores in a centrally accessible data repository. The data warehouses can include information gathered from various online transaction processing (OLTP) applications that record transactions and/or behaviors of customers when the customers interact with the organizations in some way. The information stored in the data warehouses may also include metadata information regarding the structure and relationship of the information. For example report specifications may be stored that describe information to be presented for a particular report. Additional information may be stored regarding relational models of the information, Dimensional models and Online Analytical Processing (OLAP) cube models as well as other information.

Moreover, organizations deploy a variety of business intelligence reports that allow the organization to use reporting tools, such as OLAP tools to create dimensions, metrics, filters, and templates associated with searching, retrieving, analyzing and viewing the organizations' data. The created dimensions, metrics, filters, and templates combine to form the business intelligence reports that process against the organizations' data in order to display results in tables and/or graphs. Further, the dimensions, metrics, filters, and templates are stored in a metadata format for use by a specific OLAP tool.

Current search and retrieval techniques in business systems focus on returning objects using universal full-text methods. Currently none of these systems optimize results based on how the different objects relate to each other and how they are used in a declarative system, either by the individual user or as a whole. Full-text search results typically need to be combed through in larger volumes and individually evaluated based on how well they match the underlying meaning of the query.

There is therefore a need for methods that better generate query based on the relationship of the different objects relevance of search results for business intelligence content.

SUMMARY

According to an aspect of the patent disclosure there is provided a computer-implemented method for optimizing search results in a business intelligence system, the method comprising: selecting a first member in the business intelligence system, the business intelligence system having a user space, a content space, a data space, a master-data space and a metadata space; determining a relationship between the first member and a plurality of objects selected from the group consisting of the user space, the content space, the data space, the master-data space, the metadata space and a combination thereof; calculating a ranking of the member based on the relationship; determining a relevance of the object in the business intelligence system using the ranking; and optimizing search results of the business intelligence system using the relevance of the object.

According to another aspect of the patent disclosure there is provided a computer readable medium storing instructions or statements for use in the execution in a computer of the above method.

According to another aspect of the patent disclosure there is provided a computer system for optimizing search results in a business intelligence system, the computer system comprising: means for selecting a first member in the business intelligence system, the business intelligence system having a user space, a content space, a data space, a master-data space and a metadata space; means for determining a relationship between the first member and a plurality of objects in one space selected from the group consisting of the user space, the content space, the data space, the master-data space, the metadata space and a combination thereof; means for calculating a ranking of the member based on the relationship; means for determining a relevance of the member in the business intelligence system using the ranking; and means for optimizing search results of the business intelligence system using the relevance of the object.

Preferably, the relationship is transitive.

Preferably, the relationship is within one space selected from the group consisting of the user space, the content space, the data space, the master-data space, and the metadata space.

Preferably, the relationship is based on a popularity of the first object.

Preferably, the ranking is adjusted.

Preferably, the ranking is adjusted when two objects of the content space are used in a dash board.

Preferably, the ranking is calculated at query time.

Preferably, the ranking is calculated at indexing time.

Preferably, the ranking is further based on characteristics of a user.

Preferably, the relationship includes one space selected from the group consisting of: citation, combination, subordination, peer, instance, subscription and external reference.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of the patent disclosure will become more apparent from the following description in which reference is made to the appended drawings wherein:

FIG. 1 shows a business intelligence system in which the embodiments of the present patent disclosure may be practiced;

FIG. 2 illustrates relationships between stored business intelligence content;

FIG. 3 shows exemplary relationships between stored content in different spaces;

FIG. 4 depicts a flow chart of determining a relevance of an object;

FIG. 5 shows examples of relationships in a business intelligence system; and

FIG. 6 shows a generic computing environment in which the present patent disclosure may be implemented.

DETAILED DESCRIPTION OF EMBODIMENTS

The present patent disclosure relates to improving the relevance of search results for business intelligence content. Search results may be displayed to a business intelligence system user and ordered based on their determined relevance.

As will be appreciated by one skilled in the art, the present invention may be embodied as a system, method or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, the present invention may take the form of a computer program product embodied in any tangible medium of expression having computer-usable program code embodied in the medium.

Any combination of one or more computer usable or computer readable medium(s) may be utilized. The computer-usable or computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CDROM), an optical storage device, a transmission media such as those supporting the Internet or an intranet, or a magnetic storage device. Note that the computer-usable or computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. In the context of this document, a computer-usable or computer-readable medium may be any medium that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-usable medium may include a propagated data signal with the computer-usable program code embodied therewith, either in base-band or as part of a carrier wave. The computer usable program code may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc.

Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

The present invention is described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

Using the described embodiments of the present patent disclosure, business intelligence users searching for information in business intelligence systems and related data stores, for example structured or unstructured data stores, can more efficiently and accurately locate the desired information by searching using terms they are familiar with and, at the same time, by relying on the business intelligence system to rank the results using the collective intelligence of the business intelligence system, for example but not limited to, the usage behaviour of the individual user and larger user-base as whole. This allows for leveraging known relationships to adjust the rankings of the different objects, and their related terms in the business intelligence system.

FIG. 1 shows a business intelligence system in which the embodiments of the present patent disclosure may be practiced. The business intelligence system 100 includes a plurality of spaces to describe possible arrangement of content stored in a business intelligence system. The business intelligence system 100 includes, for example but not limited to, a user space 102, a content space 104, a data space 108, a master-data space 110 and a metadata space 112. As illustrated in FIG. 1, users generally interacts with the content space, for example, a user may define a layout of a business intelligence report. A business intelligence report may in turn be defined by the objects in the data space 108, master-data space 110 and metadata space 112. Members of the user space 102 may include, for example, a user 130, a subordinate 132 of the user 130. Objects of the content space 104 may include, for example, business intelligence reports such as “inventory in Asia” 128; “margin in Asia” 126; “revenue by country” 127; and “margin in Europe” 124. Objects of the data space 108 may include, for example, “Asia” 114, “Europe” 116 and “Canada” 115. Objects of the metadata space 112 include, for example, “inventory” 118, “regions” 120, “countries” 121 and “margin” 122. Metadata in a business intelligence system have been described, for example, in U.S. Pat. No. 6,662,188 “Metadata model” to Rasmussen et al., and U.S. Pat. No. 6,609,123 “Query engine and method for querying data using metadata model” to Cazemier et al., which are incorporated by reference in their entireties. Master data in the master data space 110 are generally reference data describing a physical or virtual object and its properties, and shared over a number of systems. Collecting, aggregating, matching, consolidating and distributing master data throughout the systems is provided by a master data management to ensure consistency and control in the ongoing maintenance and application use of this information.

These objects or business intelligence content can be retrieved for a given search query such as people, data, metadata, reports, etc. The objects grouped into different business intelligence spaces may be related to each other in different ways. If the stored objects are treated independently, full-text search results may give acceptable results, however the search does not leverage known business intelligence relationships that are stored.

FIG. 2 shows relationships between stored business intelligence content. Many one-way relationships are transitive: if user A has a particular one-way relationship with user B, and user B has a similar one-way relationship with user C, then if the relationship is transitive it can be inferred that user A has this same one-way relationship with user C.

The embodiments of the present patent disclosure leverage the above described declared relationships as to improve ranking. Referring to FIG. 5, the relationships may include, but not limited to:

-   Citation 502: for example, the member “Canada” 115 may refer to or     drill to the member “Countries” in metadata space 121. Other     examples of citation include usage tracking as objects are selected     for viewing or further use. -   Combination 504: two originally unrelated objects, for example,     “Margin in Europe” 124 and “Margin in Asia” 126 are combined by a     user into a composite report, portal, or dashboard. -   Subordination 506: for example, a user reporting and responsibility     structure. A ranking may be influenced inversely to the standard     method, such as the case where all subordinates 132 are interested     in what the superior 130 is interested in. -   Peer 508: example include: employee responsibility area, level,     geography, department. Instance 128, 122: example include: stored     output of a report “Inventory in Asia”, data instance of a metadata     type “Margin” 122. -   Subscription 510: for example, a user 130 regularly reads a report     127. -   External references 512: for example, a given term's “Asia” 114     popularity in an unstructured system or linguistic ontology.

Using stock full-text with the term “Canada” would result in determining that the term “Canada” is in a particular database table. On the other side, the transitive relationship may be leveraged to traverse this graph and return the report “Revenue by Country” 127 as a result, given the direct relationships 202, 204 between the “Revenue by Country” 127 report and term “Canada” 115.

In addition to using the transitive relationships 202, 204 described above, the embodiments of the present patent disclosure leverage the user space 102, or relationships within a given space. The additional relationship information may be used to indicate, for example, that multiple objects in the content space 104 are being used in a given report, portal or dashboard, or the popularity of a given report within a reporting hierarchy, or the popularity of a given report as a citation or drill target.

FIG. 3 shows exemplary relationships between stored content in different spaces. The relationships may be used as a leverage to provide improved search results. One embodiment of the present patent disclosure uses the entire object set of a given business intelligence system as a network of nodes contained within a variety of different spaces. The objects in the user space 102, content space 104, data space 108, master-data space 110 and metadata space 112, for example, “Asia” 114, “Inventory in Asia” 128, may be considered as the nodes of the network, while the relationships, for example, between “Inventory in Asia” 128 and “Asia” 114 may be considered as the vertices of the network. The nodes are then assigned a given ranking based on their relationships within a space as well as between spaces. These rankings are intended to indicate a degree of semantic knowledge of the value of a given business intelligence system.

Referring to FIG. 4, the ranking may be adjusted upon usage of the business intelligence system, for example, as more users subscribe to a given report, the ranking of the report increases. Likewise, when two reports are used in the same dashboard, their rankings will increase as will their related metadata and data. In other words, any selected member 402 in the spaces of the business intelligence system 100 may have a ranking calculated 408 based on the relationship of the member 404. The relevance of the member may then be determined based on the ranking 410. The searching system can learn and be tuned to provide better business intelligence search results 412.

The rankings may also be calculated, on-the-fly at query time or during indexing, for individual users, based on that user's characteristics 406. If, for example, a given user is subscribed to multiple reports about inventory and the Asia-Pacific region, objects that relate to those will have a higher calculated ranking. If that user also manages someone who subscribes to reports about Europe and margin, those objects will have higher rankings, however less so than the direct case as they sit out one extra step from the individual.

Referring back to FIG. 3, report “Margin in Asia” 126 has a boosted ranking, as indicated by increased size of the object. Neither the user 130 nor the subordinate 132 is subscribed to this report, however it is considered more relevant to the user 130 because it relates to a topic that matters to the user's subordinate 132. In this fashion the entire network can have associated rankings that accurately indicate usage, and evolve as usage evolves.

The exemplary system 600 may further include a hard disk drive 624 for reading from and writing to a hard disk, connected to the I/O bus via a hard disk interface 640, and an optical disk drive 642 for reading from or writing to a removable optical disk 644 such as a CD-ROM or other optical media. The hard disk drive 624, and optical disk drive 642 may be connected to the I/O bus 612 by a hard disk drive interface 640, and an optical drive interface 646, respectively. The drives and their associated computer-readable media provide non-volatile storage of computer readable instructions, data structures, program modules and other data for the system 600. Although the exemplary environment described herein employs a hard disk 624 and a removable optical disk 644, it should be appreciated by those skilled in the art that other types of computer readable media which can store data that is accessible by a computer, such as magnetic cassettes, flash memory cards, digital video disks, Bernoulli cartridges, random access memories (RAMs), read-only memories (ROMs) and the like may also be used in the exemplary operating environment.

A number of program modules may be stored on the hard disk 624, optical disk 644, ROM 614 or RAM 616, including an operating system 648, one or more application programs 650, other program modules 652 and program data 654.

FIG. 6 and the following discussion are intended to provide a brief general description. FIG. 6 illustrates a block diagram of a suitable computing environment in which an embodiment of the present patent disclosure may be implemented.

Those skilled in the art will appreciate that the patent disclosure may be practiced with many computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers and the like. The patent disclosure may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

Although not required, the patent disclosure will be described in the general context of computer-executable instructions, such as program modules, being executed by a personal computer. Generally, program modules include routines, programs, objects, components, data structures and the like that perform particular tasks or implement particular abstract data types.

With reference to FIG. 6, an exemplary system 600 for implementing the patent disclosure may be, for example, one of the general purpose computers. The system 600 includes processor 602, which in the exemplary embodiment are each connected to cache memory 604, the cache 604 is connected in turn to a system bus 606 that couples various system components.

Also connected to system bus 606 are a system memory 608 and a host bridge 610. Host bridge 610 connects I/O bus 612 to system bus 606, relaying and/or transforming data transactions from one bus to the other. The system bus 606 and the I/O bus 612 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. The system memory includes read-only memory (ROM) 614 and random access memory (RAM) 616. A basic input/output system 618 (BIOS), containing the basic routines that help to transfer information between elements within the personal computer 600, such as during start-up, is stored in ROM 614.

In the exemplary embodiment, the system 600 may further include a graphics adapter 620 connected to I/O bus 612, receiving user interface information for display device 622. A user may enter commands and information into the system 600 through input devices 630 such as a conventional mouse, a keyboard 630, or the like. Other input devices 634 may include a microphone, joystick, game pad, satellite dish, scanner or the like. The devices may be connected via an Industry Standard Architecture (ISA) bridge 626, or a Universal Serial Bus (USB) bridge 632 to I/O bus 612, respectively. PCI device such as a modem 638 may be connected to the I/O bus 612 via PCI bridge 636.

The exemplary system 600 may further include a hard disk drive 624 for reading from and writing to a hard disk, connected to the I/O bus via a hard disk interface 640, and an optical disk drive 642 for reading from or writing to a removable optical disk 644 such as a CD-ROM or other optical media. The hard disk drive 624, magnetic disk drive 28, and optical disk drive 642 may be connected to the I/O bus 612 by a hard disk drive interface 640, and an optical drive interface 646, respectively. The drives and their associated computer-readable media provide non-volatile storage of computer readable instructions, data structures, program modules and other data for the system 600. Although the exemplary environment described herein employs a hard disk 624 and a removable optical disk 644, it should be appreciated by those skilled in the art that other types of computer readable media which can store data that is accessible by a computer, such as magnetic cassettes, flash memory cards, digital video disks, Bernoulli cartridges, random access memories (RAMs), read-only memories (ROMs) and the like may also be used in the exemplary operating environment.

A number of program modules may be stored on the hard disk 624, optical disk 644, ROM 618 or RAM 616, including an operating system 648, one or more application programs 650, other program modules 652 and program data 654.

The exemplary system 600 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 656. The remote computer 656 may be another personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the exemplary system 600. The logical connections depicted in FIG. 6 include a network 658, for example, a local area network (LAN) or a wide area network (WAN). Such networking environments are commonplace in offices, enterprise-wide computer networks, Intranets and the Internet.

When used in a networking environment, the exemplary system 600 is connected to the local network 658 through a network interface or adapter 660. The exemplary system 600 may use the modem 638 or other means for establishing communications 662 over a wide area network such as the Internet. In a networked environment, program modules depicted relative to the exemplary system 600, or portions thereof, may be stored in the remote memory storage device. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used.

The exemplary embodiment shown in FIG. 6 is provided solely for the purposes of explaining the patent disclosure and those skilled in the art will recognize that numerous variations are possible, both in form and function. For instance, the exemplary system 600 may also include a magnetic disc drive, and numerous other optional components. All such variations are believed to be within the spirit and scope of the present invention. The exemplary system 600 and the exemplary figures below are provided solely as examples for the purposes of explanation and are not intended to imply architectural limitations. In fact, this method and system can be easily adapted for use on any programmable computer system, or network of systems, on which software applications can be executed.

Embodiments within the scope of the present patent disclosure can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations thereof. Apparatus within the scope of the present patent disclosure can be implemented in a computer program product tangibly embodied in a machine-readable storage device for execution by a programmable processor; and method actions within the scope of the present patent disclosure can be performed by a programmable processor executing a program of instructions to perform functions of the patent disclosure by operating on input data and generating output. Embodiments within the scope of the present patent disclosure be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device. Each computer program can be implemented in a high-level procedural or object oriented programming language, or in assembly or machine language if desired; and in any case, the language can be a compiled or interpreted language. Suitable processors include, by way of example, both general and special purpose microprocessors. Generally, a processor will receive instructions and data from a read-only memory and/or a random access memory. Generally, a computer will include one or more mass storage devices for storing data files. Embodiments within the scope of the present patent disclosure include computer-readable media for carrying or having computer-executable instructions, computer-readable instructions, or data structures stored thereon. Such computer-readable media may be any available media, which is accessible by a general-purpose or special-purpose computer system. Examples of computer-readable media may include physical storage media such as RAM, ROM, EPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other media which can be used to carry or store desired program code means in the form of computer-executable instructions, computer-readable instructions, or data structures and which may be accessed by a general-purpose or special-purpose computer system. Any of the foregoing can be supplemented by, or incorporated in, ASICs (application-specific integrated circuits). While particular embodiments of the present patent disclosure have been shown and described, changes and modifications may be made to such embodiments without departing from the true scope of the invention.

Reference will now be made in detail to some specific embodiments of the patent disclosure including the best modes contemplated by the inventors for carrying out the invention. Examples of these specific embodiments are illustrated in the accompanying drawings. While the patent disclosure is described in conjunction with these specific embodiments, it will be understood that it is not intended to limit the patent disclosure to the described embodiments. On the contrary, it is intended to cover alternatives, modifications, and equivalents as may be included within the spirit and scope of the patent disclosure as defined by the appended claims. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The present patent disclosure may be practiced without some or all of these specific details. In other instances, well-known process operations have not been described in detail in order not to unnecessarily obscure the present invention.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present patent disclosure has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the patent disclosure in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. The embodiment was chosen and described in order to best explain the principles of the patent disclosure and the practical application, and to enable others of ordinary skill in the art to understand the patent disclosure for various embodiments with various modifications as are suited to the particular use contemplated. 

1. A computer-implemented method for optimizing search results in a business intelligence system, the method comprising: selecting one or more objects in the business intelligence system, the business intelligence system having a user space including one or more objects with user information, a content space including one or more objects with content layout information, a data space including one or more objects with information defining content, a master-data space including one or more objects with information describing objects and a metadata space including one or more objects with metadata, wherein one or more relationships link the objects in the business intelligence system; determining a relationship between the selected one or more objects and other objects from at least one of the user space, the content space, the data space, the master-data space, and the metadata space, wherein at least one of the other objects resides within a different space than the space containing a corresponding selected object; calculating a ranking of the selected one or more objects based on user activity with the selected one or more objects and user activity with the other objects related by the determined relationship, wherein the ranking provides an indication of a degree of relevance for the selected one or more objects; repeatedly updating the ranking of the selected one or more objects in response to usage of the business intelligence system; and searching the business intelligence system having the determined ranking of the selected one or more objects to produce optimized search results, wherein the determined relationship between the selected one or more objects and other objects is utilized to identify the other objects for the search results.
 2. The computer-implemented method as claimed in claim 1, wherein the determined relationship is transitive.
 3. The computer-implemented method as claimed in claim 1, wherein the relationship is determined within a space selected from the group consisting of the user space, the content space, the data space, the master-data space, and the metadata space.
 4. The computer-implemented method as claimed in claim 1, wherein the determined relationship is based on a popularity of a selected object.
 5. The computer-implemented method as claimed in claim 1, wherein the ranking is adjusted when two objects of the content space are used in a dash board.
 6. The computer-implemented method as claimed in claim 1, wherein the ranking is calculated at query time.
 7. The computer-implemented method as claimed in claim 1, wherein the ranking is calculated at indexing time.
 8. The computer-implemented method as claimed in claim 1, wherein the ranking is further based on characteristics of a user.
 9. The computer-implemented method as claimed in claim 1, wherein the determined relationship includes one member selected from the group consisting of: citation, combination, subordination, peer, instance, subscription and external reference.
 10. A computer readable memory device storing instructions or statements for use in the execution in a computer of a method for optimizing search results in a business intelligence system, the method comprising: selecting one or more objects in the business intelligence system, the business intelligence system having a user space including one or more objects with user information, a content space including one or more objects with content layout information, a data space including one or more objects with information defining content, a master-data space including one or more objects with information describing objects and a metadata space including one or more objects with metadata, wherein one or more relationships link the objects in the business intelligence system; determining a relationship between the selected one or more objects and other objects from at least one of the user space, the content space, the data space, the master-data space, and the metadata space, wherein at least one of the other objects resides within a different space than the space containing a corresponding selected object; calculating a ranking of the selected one or more objects based on user activity with the selected one or more objects and user activity with the other objects related by the determined relationship, wherein the ranking provides an indication of a degree of relevance for the selected one or more objects; repeatedly updating the ranking of the selected one or more objects in response to usage of the business intelligence system; and searching the business intelligence system having the determined ranking of the selected one or more objects to produce optimized search results, wherein the determined relationship between the selected one or more objects and other objects is utilized to identify the other objects for the search results.
 11. The computer readable memory device as claimed in claim 10, wherein the relationship is determined within a space selected from the group consisting of the user space, the content space, the data space, the master-data space, and the metadata space.
 12. The computer readable memory device as claimed in claim 10, wherein the determined relationship is based on a popularity of a selected object.
 13. The computer readable memory device as claimed in claim 10, wherein the ranking is adjusted when two objects of the content space are used in a dash board.
 14. A computer system for optimizing search results in a business intelligence system, the computer system comprising: a processor configured for: selecting one or more objects in the business intelligence system, the business intelligence system having a user space including one or more objects with user information, a content space including one or more objects with content layout information, a data space including one or more objects with information defining content, a master-data space including one or more objects with information describing objects and a metadata space including one or more objects with metadata, wherein one or more relationships link the objects in the business intelligence system; determining a relationship between the selected one or more objects and other objects from at least one of the user space, the content space, the data space, the master-data space, and the metadata space, wherein at least one of the other objects resides within a different space than the space containing a corresponding selected object; calculating a ranking of the selected one or more objects based on user activity with the selected one or more objects and user activity with the other objects related by the determined relationship, wherein the ranking provides an indication of a degree of relevance for the selected one or more objects; repeatedly updating the ranking of the selected one or more objects in response to usage of the business intelligence system; and searching the business intelligence system having the determined ranking of the selected one or more objects to produce optimized search results, wherein the determined relationship between the selected one or more objects and other objects is utilized to identify the other objects for the search results.
 15. The computer system as claimed in claim 14, wherein the relationship is determined within a space selected from the group consisting of the user space, the content space, the data space, the master-data space, and the metadata space.
 16. The computer system as claimed in claim 14, wherein the determined relationship is based on a popularity of a selected object.
 17. The computer system as claimed in claim 14, wherein the ranking is adjusted when two objects of the content space are used in a dash board. 